This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. One of the primary scientific problems in our laboratory is tracing white matter connectivity in the brain. We are using recently developed diffusion weighted imaging (DWI) technology, which provides an unprecedented view of anatomical connectivity in the living human brain. The most popular DWI modeling method is diffusion tensor imaging (DTI). Unfortunately, this method is severely limited in its ability to resolve white matter tract crossings, which occur quite often in the human brain (Alexander et al., 2002). We will use advanced DWI modeling methods, such as PAS-MRI, Q-Ball, and probabilistic tractography, to more accurately resolve white matter tract crossings and anatomical connectivity between brain regions. We plan to use supercomputing resources mostly for the computationally intensive PAS-MRI algorithm (based on maximum-entropy spherical deconvolution;Jansons et al., 2003 and Alexander et al., 2005). Resolving white matter tract crossings with this algorithm takes one minute per voxel on modern desktop computers. With 786432 voxels (128 X 128 in-plane, and 48 slices) it would take 546 days to compute just one subjects white matter tractography. We hope using supercomputing resources will make this a more practical endeavor. We plan to try several machines on the TeraGrid to explore using a Java program (Camino) across a large number of processors simultaneously. We also would like to find the best TeraGrid machine for tracing white matter tracts in high-resolution brain images, which is more computationally intensive. Finally, we hope to use this DAC-TG to test our programs and prepare for submitting an MRAC in January.